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Network analysis of the association between depression and quality of life in the elderly.

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Title: Network analysis of the association between depression and quality of life in the elderly.
Authors: Xu, Yuan (AUTHOR), Liang, Yu-Ting (AUTHOR), Li, Jian-Wei (AUTHOR), Li, Teng-Fei (AUTHOR), Li, Jie (AUTHOR), Qin, Qi-Rong (AUTHOR)
Source: Psychology, Health & Medicine. Jan2026, Vol. 31 Issue 1, p155-169. 15p.
Subjects: Cross-sectional method, Lifestyles, Research funding, Descriptive statistics, Quality of life, Sociodemographic factors, Data analysis software, Psychological tests, Mental depression, Active aging, Old age
Abstract: The worsening global aging population and the rising prevalence of depression occur simultaneously. However, the mechanisms through which depression affects quality of life (QOL) in different domains remain poorly understood, particularly in older adults. Data for this research were sourced from the Healthy Aging Cross-Sectional Data. To assess depression symptoms and QOL, the Geriatric Depression Scale (GDS-15) and the World Health Organization Quality of Life Brief Version (WHOQOL-BREF) were utilized, respectively. The analysis sought to evaluate the influence of depression on QOL by examining central and bridging symptoms within the network and their connections to QOL. A total of 2,520 participants were included in this survey, of which 581 (23.1%) screened positive for depression (GDS-15 ≥ 5). From the analyses of global network comparison, we found that the networks appeared to differ between the non-depressed and depressed groups both before (M = 0.208, p = 0.022, S = 0.526, p = 0.422) and after (M = 0.216, p = 0.036, S = 0.091, p = 0.806) propensity score matching (PSM). Within the derived depression-QOL network, we identified that the 10 strongest edges between the two communities are distributed across the respective domains of QOL. Notably, GDS1 (Life satisfaction), GDS5 (Happiness), and GDS4 (Boredom) serve as bridge symptoms within the depression-QOL network. The indicator of 'a general sense of satisfaction with life' was crucial in the network of symptoms, demonstrating notable links to the QOL of the residents. Vigilance towards these symptoms is vital for reducing risks and preventing the worsening of QOL in the elderly. [ABSTRACT FROM AUTHOR]
Copyright of Psychology, Health & Medicine is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Network analysis of the association between depression and quality of life in the elderly.
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  Data: <searchLink fieldCode="AR" term="%22Xu%2C+Yuan%22">Xu, Yuan</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liang%2C+Yu-Ting%22">Liang, Yu-Ting</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Jian-Wei%22">Li, Jian-Wei</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Teng-Fei%22">Li, Teng-Fei</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Jie%22">Li, Jie</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Qin%2C+Qi-Rong%22">Qin, Qi-Rong</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Psychology%2C+Health+%26+Medicine%22">Psychology, Health & Medicine</searchLink>. Jan2026, Vol. 31 Issue 1, p155-169. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Cross-sectional+method%22">Cross-sectional method</searchLink><br /><searchLink fieldCode="DE" term="%22Lifestyles%22">Lifestyles</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+of+life%22">Quality of life</searchLink><br /><searchLink fieldCode="DE" term="%22Sociodemographic+factors%22">Sociodemographic factors</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+tests%22">Psychological tests</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+depression%22">Mental depression</searchLink><br /><searchLink fieldCode="DE" term="%22Active+aging%22">Active aging</searchLink><br /><searchLink fieldCode="DE" term="%22Old+age%22">Old age</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: The worsening global aging population and the rising prevalence of depression occur simultaneously. However, the mechanisms through which depression affects quality of life (QOL) in different domains remain poorly understood, particularly in older adults. Data for this research were sourced from the Healthy Aging Cross-Sectional Data. To assess depression symptoms and QOL, the Geriatric Depression Scale (GDS-15) and the World Health Organization Quality of Life Brief Version (WHOQOL-BREF) were utilized, respectively. The analysis sought to evaluate the influence of depression on QOL by examining central and bridging symptoms within the network and their connections to QOL. A total of 2,520 participants were included in this survey, of which 581 (23.1%) screened positive for depression (GDS-15 ≥ 5). From the analyses of global network comparison, we found that the networks appeared to differ between the non-depressed and depressed groups both before (M = 0.208, p = 0.022, S = 0.526, p = 0.422) and after (M = 0.216, p = 0.036, S = 0.091, p = 0.806) propensity score matching (PSM). Within the derived depression-QOL network, we identified that the 10 strongest edges between the two communities are distributed across the respective domains of QOL. Notably, GDS1 (Life satisfaction), GDS5 (Happiness), and GDS4 (Boredom) serve as bridge symptoms within the depression-QOL network. The indicator of 'a general sense of satisfaction with life' was crucial in the network of symptoms, demonstrating notable links to the QOL of the residents. Vigilance towards these symptoms is vital for reducing risks and preventing the worsening of QOL in the elderly. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Psychology, Health & Medicine is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/13548506.2025.2519246
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      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 155
    Subjects:
      – SubjectFull: Cross-sectional method
        Type: general
      – SubjectFull: Lifestyles
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Quality of life
        Type: general
      – SubjectFull: Sociodemographic factors
        Type: general
      – SubjectFull: Data analysis software
        Type: general
      – SubjectFull: Psychological tests
        Type: general
      – SubjectFull: Mental depression
        Type: general
      – SubjectFull: Active aging
        Type: general
      – SubjectFull: Old age
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    Titles:
      – TitleFull: Network analysis of the association between depression and quality of life in the elderly.
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            NameFull: Xu, Yuan
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              M: 01
              Text: Jan2026
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              Y: 2026
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